Adaptive trust-region algorithms for unconstrained optimization

DOI10.1080/10556788.2019.1698578zbMath1494.90112OpenAlexW2996444651MaRDI QIDQ5865332

Thomas J. Asaki, Mostafa Rezapour

Publication date: 13 June 2022

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556788.2019.1698578

zbMATH Keywords

unconstrained optimizationnonlinear programmingtrust-region methods

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Uses Software

• CUTEst

Cites Work

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• Global convergence of a two-parameter family of conjugate gradient methods without line search
• A retrospective trust-region method for unconstrained optimization
• Nonmonotonic trust region algorithm
• A nonmonotone adaptive trust region method and its convergence
• A quasi-Newton trust-region method
• Nonmonotone trust region method for solving optimization problems
• CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization
• The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
• A Family of Trust-Region-Based Algorithms for Unconstrained Minimization with Strong Global Convergence Properties
• Numerical Optimization
• Trust Region Methods
• A New Algorithm for Unconstrained Optimization
• An algorithm for solving linearly constrained optimization problems
• Benchmarking optimization software with performance profiles.

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